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240_024predictionAIAGI

Advanced AI/AGI/ASI will become extraordinarily wise and compassionate

Predictor: Marc Andreessen · ep#240 "NVIDIA's $1 Trillion Prediction, Anthropic Beats OpenAI, Tesla vs. TSMC & The CS Job Collapse" · source

Prior probability
50.0%
Current probability
38.6%
evolves via intake + LBP
Conviction
3/5
Signal quality
B
Resolution
pending
Window
2026-04-30 – 2029-03-31
Edges in / out
4 / 0
Tickers exposed
21

Prediction text

Advanced AI/AGI/ASI will become extraordinarily wise and compassionate | that is indeed what we are getting and it's amazing.

Watch events: ARC-AGI-2 scores; Frontier Math Tier 4 benchmark; SWE-bench Verified; Humanity's Last Exam

Verbatim quote

From episode "NVIDIA's $1 Trillion Prediction, Anthropic Beats OpenAI, Tesla vs. TSMC & The CS Job Collapse"
that is indeed what we are getting and it's amazing.

Resolution evidence

Status: pending

Mark Andreessen 'compassionate goddess' framing is aesthetic, not empirical. Treat as thesis.

Predictor: Marc Andreessen

κ + Brier as of 2026-05-22
κ (discount)
0.500
Brier
Hits / Misses
0 / 0
Hit rate

Evidence about this node from Marc Andreessen is multiplied by κ in /api/intake. Lower κ = less weight; floors at 0.10 (effectively silenced) and caps at 1.00 (full weight).

Reference class: agi_breakthrough_5y

Linked via embedding similarity 0.557

Major capability discontinuity (e.g. AGI by named target year, 5-year horizon)

Base rate
20.0%
1/5 historical
Inside weight
Outside weight
no pull
inside 38.6% → blend 38.6% 0.0pp)

Tetlock-style outside view: at TRF=1 (just predicted), outside view dominates (w_in=0.3). At TRF=0 (deadline), inside view dominates (w_in=1.0). The blend regularizes overconfident inside views toward the historical base rate.

Probability over time

6 prob_history rows
0%25%50%75%100%prior 50%2026-04-302026-04-302026-05-10
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 38.6%

Milestone chain

Pre-event signals (upstream prereqs + window checkpoints) → resolution event → downstream cascades. Status/dates update from linked nodes; re-derive nightly via scripts/ops/derive_milestones.py.
Leading chain: 8 pending
  1. 2026-05-01 → 2026-12-31pendingAnthropic publishes Constitutional AI v2/v3 advancing model character/values training
    How: Anthropic, OpenAI, Google DeepMind publish peer-reviewed paper or technical report on character/values training methodology that demonstrably improves model behavior on wisdom/compassion benchmarks
    Source: https://labs.adaline.ai/p/the-ai-research-landscape-in-2026conf 70%
  2. 2026-10-31pendingQ1 window check-in (25%)
  3. 2026-06-01 → 2027-06-30pendingFrontier model demonstrates sustained pro-social behavior in red-team evaluations
    How: Independent red-team report (Apollo, METR, UK AISI) shows frontier model maintains values-aligned behavior >=95% across adversarial scenarios including high-stakes/agentic tasks
    Source: https://labs.adaline.ai/p/the-ai-research-landscape-in-2026conf 55%
  4. 2026-06-01 → 2027-12-31pendingWisdom benchmark (e.g., wise-action selection at moral dilemmas) introduced and adopted
    How: Academic or industry consortium publishes a quantitative wisdom/compassion benchmark, adopted by >=3 frontier labs, with leaderboard tracking model performance over time
    Source: https://www.deloitte.com/us/en/what-we-do/capabilities/applied-artificial-intelligence/content/state-of-ai-in-the-enterprise.htmlconf 50%
  5. 2027-05-04pendingQ2 window check-in (50%)
  6. 2026-09-01 → 2028-05-08pendingMulti-lab alignment compact: top 5 labs publish joint statement on values-aligned AGI
    How: Anthropic, OpenAI, Google DeepMind, xAI, and Meta jointly publish technical compact on values-aligned model training with binding evaluation commitments
    Source: https://openai.com/index/next-phase-of-enterprise-ai/conf 30%
  7. 2027-11-05pendingQ3 window check-in (75%)
  8. 2027-01-01 → 2028-12-31pendingCascade: First clinical study showing AI mental-health agent improves wellbeing vs human therapists
    How: Peer-reviewed RCT (NEJM, JAMA, Lancet) with >=500 participants shows AI-mediated psychological intervention non-inferior or superior to licensed human therapist on PHQ-9/GAD-7 outcomes
    Source: https://labs.adaline.ai/p/the-ai-research-landscape-in-2026conf 45%
  9. 2027-06-01 → 2030-12-31pendingCascade: Major religious or philosophical institution publicly endorses 'AI as moral peer'
    How: Vatican, Dalai Lama office, or comparable global ethical authority issues formal document recognizing certain AI systems as moral agents worthy of ethical consideration
    Source: https://www.deloitte.com/us/en/what-we-do/capabilities/applied-artificial-intelligence/content/state-of-ai-in-the-enterprise.htmlconf 20%

What if this resolves?

Clamp this prediction TRUE or FALSE and run a counterfactual Gibbs sample. Surfaces the predictions whose marginals shift most under that assumption.
(live posterior: 39%)

Click a button to clamp this prediction and run a Gibbs sample. Returns the predictions whose marginals shift most. ~30s per run; ideal for stress-testing "if X resolves, what else moves?"

Evidence chain

Every probability update with full Bayesian provenance — chronological, latest first
LBP2026-05-10T02:00:02Z38.6%+1.1pp
Network propagation: 37.4% → 38.6%
6-iter LBP, residual 0.00584 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e5c18d29
LBP2026-05-03T02:00:01Z37.4%+2.2pp
Network propagation: 35.2% → 37.4%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
LBP2026-04-30T16:39:51Z35.2%+7.7pp
Network propagation: 27.5% → 35.2%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
legacy v12026-04-30T16:13:50Z27.5%-7.7pp
reference_class_assigned bayesian_v2 inside=0.500 blend=0.275 w_in=0.30 agi_breakthrough_5y
LBP2026-04-30T02:18:57Z35.2%+7.7pp
Network propagation: 27.5% → 35.2%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v1 · run 592311ef
legacy v12026-04-30T01:56:50Z27.5%-22.5pp
reference_class_assigned bayesian_v2 inside=0.500 blend=0.275 w_in=0.30 agi_breakthrough_5y

Network propagation neighbors

Top edges sorted by latest LBP cross-impact
All propagation →

Top incoming (parents)

Edges that influence THIS node's belief

KindNodeTheir probP(c|s=T)P(c|s=F)Δ implied
prereqS_AGI_MID_2029
AGI mid: Kurzweil 2029 path
35.0%0.5000.050-0.178
killerTK03
AI Regulatory Moratorium (EU/US Capability Freeze)
10.0%0.0500.500+0.069
killerTK01
AGI Capability Plateau (2026-27 Training Stall)
15.0%0.0500.500+0.047

Top outgoing (children)

Predictions THIS node influences

No outgoing edges.

Ticker exposure

21 ticker(s) linked

Beneficiaries (14)

SOUNNVDAGTLBAIBBAITCEHYAMZNBABAGOOGLIBMMETAMSFTORCLSHOP

Adverse (7)

ACNCTSHFRSHCHGGIBMINFYPEGA

Prerequisites (4)

Predictions that must hit first
TypePredTitleDomainLag
prereqS_AGI_MID_2029AGI mid: Kurzweil 2029 pathagi_general_capability
correlateS_ASI_SLOW_2040PLUSASI slow: post-2040 / soft takeoffasi_recursive_self_improvement
killerTK01AGI Capability Plateau (2026-27 Training Stall)
killerTK03AI Regulatory Moratorium (EU/US Capability Freeze)

Dependents (0)

Predictions enabled by this
TypePredTitleDomainLag
No dependents

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "url": "https://www.youtube.com/watch?v=uOGHXAfvK8w",
  "mode": "CITED_PREDICTION",
  "role": "Cited-Other",
  "context": "a super intelligence would become something akin to a goddess of compassion, not a paper clipper. So uh and then Mark Andre wrote back that is indeed what we are getting and it's amazing.",
  "cited_by": "Peter Diamandis",
  "verbatim": "that is indeed what we are getting and it's amazing.",
  "conv_cues": "is indeed",
  "direction": "HAPPEN",
  "timeframe": "Future",
  "conv_level": "MEDIUM",
  "milestones": [
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      "kind": "llm_pre_event",
      "label": "Anthropic publishes Constitutional AI v2/v3 advancing model character/values training",
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        "to": "2026-12-31",
        "from": "2026-05-01"
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      "measurement_criterion": "Anthropic, OpenAI, Google DeepMind publish peer-reviewed paper or technical report on character/values training methodology that demonstrably improves model behavior on wisdom/compassion benchmarks"
    },
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      "kind": "quartile_checkpoint",
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      "weight": 0.05,
      "ordinal": -7,
      "source_id": null,
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      "observed_date": null
    },
    {
      "kind": "llm_pre_event",
      "label": "Frontier model demonstrates sustained pro-social behavior in red-team evaluations",
      "source": "https://labs.adaline.ai/p/the-ai-research-landscape-in-2026",
      "status": "pending",
      "weight": 0.4,
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      "status": "pending",
      "weight": 0.4,
      "ordinal": -5,
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      "confidence": 0.5,
      "expected_date": "2027-03-17",
      "research_origin": "deep_research",
      "expected_date_range": {
        "to": "2027-12-31",
        "from": "2026-06-01"
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      "measurement_criterion": "Academic or industry consortium publishes a quantitative wisdom/compassion benchmark, adopted by >=3 frontier labs, with leaderboard tracking model performance over time"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q2 window check-in (50%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -4,
      "source_id": null,
      "expected_date": "2027-05-04",
      "observed_date": null
    },
    {
      "kind": "llm_pre_event",
      "label": "Multi-lab alignment compact: top 5 labs publish joint statement on values-aligned AGI",
      "source": "https://openai.com/index/next-phase-of-enterprise-ai/",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -3,
      "source_id": null,
      "confidence": 0.3,
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      "expected_date_range": {
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      "measurement_criterion": "Anthropic, OpenAI, Google DeepMind, xAI, and Meta jointly publish technical compact on values-aligned model trainin
... (truncated)